The electronically steerable parasitic array radiator antenna for wireless communications : signal processing and emerging techniques

Smart antenna technology is expected to play an important role in future wireless communication networks in order to use the spectrum efficiently, improve the quality of service, reduce the costs of establishing new wireless paradigms and reduce the energy consumption in wireless networks. Generally, smart antennas exploit multiple widely spaced active elements, which are connected to separate radio frequency (RF) chains. Therefore, they are only applicable to base stations (BSs) and access points, by contrast with modern compact wireless terminals with constraints on size, power and complexity. This dissertation considers an alternative smart antenna system the electronically steerable parasitic array radiator (ESPAR) which uses only a single RF chain, coupled with multiple parasitic elements. The ESPAR antenna is of significant interest because of its flexibility in beamforming by tuning a number of easy-to-implement reactance loads connected to parasitic elements; however, parasitic elements require no expensive RF circuits. This work concentrates on the study of the ESPAR antenna for compact transceivers in order to achieve some emerging techniques in wireless communications. The work begins by presenting the work principle and modeling of the ESPAR antenna and describes the reactance-domain signal processing that is suited to the single active antenna array, which are fundamental factors throughout this thesis. The major contribution in this chapter is the adaptive beamforming method based on the ESPAR antenna. In order to achieve fast convergent beamforming for the ESPAR antenna, a modified minimum variance distortionless response (MVDR) beamfomer is proposed. With reactance-domain signal processing, the ESPAR array obtains a correlation matrix of receive signals as the input to the MVDR optimization problem. To design a set of feasible reactance loads for a desired beampattern, the MVDR optimization problem is reformulated as a convex optimization problem constraining an optimized weight vector close to a feasible solution. Finally, the necessary reactance loads are optimized by iterating the convex problem and a simple projector. In addition, the generic algorithm-based beamforming method has also studied for the ESPAR antenna. Blind interference alignment (BIA) is a promising technique for providing an optimal degree of freedom in a multi-user, multiple-inputsingle-output broadcast channel, without the requirements of channel state information at the transmitters. Its key is antenna mode switching at the receive antenna. The ESPAR antenna is able to provide a practical solution to beampattern switching (one kind of antenna mode switching) for the implementation of BIA. In this chapter, three beamforming methods are proposed for providing the required number of beampatterns that are exploited across one super symbol for creating the channel fluctuation patterns seen by receivers. These manually created channel fluctuation patterns are jointly combined with the designed spacetime precoding in order to align the inter-user interference. Furthermore, the directional beampatterns designed in the ESPAR antenna are demonstrated to improve the performance of BIA by alleviating the noise amplification. The ESPAR antenna is studied as the solution to interference mitigation in small cell networks. Specifically, ESPARs analog beamforming presented in the previous chapter is exploited to suppress inter-cell interference for the system scenario, scheduling only one user to be served by each small BS at a single time. In addition, the ESPAR-based BIA is employed to mitigate both inter-cell and intracell interference for the system scenario, scheduling a small number of users to be simultaneously served by each small BS for a single time. In the cognitive radio (CR) paradigm, the ESPAR antenna is employed for spatial spectrum sensing in order to utilize the new angle dimension in the spectrum space besides the conventional frequency, time and space dimensions. The twostage spatial spectrum sensing method is proposed based on the ESPAR antenna being targeted at identifying white spectrum space, including the new angle dimension. At the first stage, the occupancy of a specific frequency band is detected by conventional spectrum-sensing methods, including energy detector and eigenvalue-based methods implemented with the switched-beam ESPAR antenna. With the presence of primary users, their directions are estimated at the second stage, by high-resolution angle-of-arrival (AoA) estimation algorithms. Specifically, the compressive sensing technology has been studied for AoA detection with the ESPAR antenna, which is demonstrated to provide high-resolution estimation results and even to outperform the reactance-domain multiple signal classification

Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems with Limited Feedback Using ESPAR Antennas

We consider an opportunistic cognitive radio (CR) system consisting of a primary user (PU), secondary transmitter (SUtx), and secondary receiver (SUrx), where SUtx is equipped with an electrically steerable parasitic array radiator (ESPAR) antenna with the capability of choosing one beam among M beams for sensing and communication, and there is a limited feedback channel from SUrx to SUtx. Taking a holistic approach, we develop a framework for integrated sector-based spectrum sensing and sector-based data communication. Upon sensing the channel busy, SUtx determines the beam corresponding to PU's orientation. Upon sensing the channel idle, SUtx transmits data to SUrx, using the selected beam corresponding to the strongest channel between SUtx and SUrx. We formulate a constrained optimization problem, where SUtx-SUrx link ergodic capacity is maximized, subject to average transmit and interference power constraints, and the optimization variables are sensing duration, thresholds of channel quantizer at SUrx, and transmit power levels at SUtx. Since this problem is non-convex we develop a suboptimal computationally efficient iterative algorithm to find the solution. Our results demonstrate that our CR system yields a significantly higher capacity, and lower outage and symbol error probabilities, compared with a CR system that its SUtx has an omni-directional antenna.Comment: This paper has been submitted to IEEE Transactions on Cognitive Communications and Networkin

Experimental Evaluation of Blind Interference Alignment

The proceeding at: 2015 Vehicular Technology Conference (VTC Spring) took place 11-14 May in Glasgow, Ireland.An experimental evaluation of Blind Interference Alignment (BIA) over a hardware platform is presented in this work. In contrast to other transmission techniques such as Linear Zero Forcing Beamforming (LZFB) or Interference Alignment (IA), BIA achieves a growth in Degrees of Freedom (DoF) without channel state information at the transmitter (CSIT). A real implementation based on Orthogonal Frequency Division Multiplexing (OFDM) and LTE parameters is implement on a testbed made up of a transmitter equipped with two antennas and two users equipped with a reconfigurable antenna each. Furthermore, a full CSIT technique such as LZFB is also implemented for comparison purposes. First, the theoretic achievable rates are obtained for both techniques. After that, the bit error rate of both schemes is evaluated regarding the achieved sum-thorughput.This work has been partially funded by research projects COMONSENS (CSD2008-00010), and GRE3N (TEC2011-29006-C03-02)

On the choice of blind interference alignment strategy for cellular systems with data sharing

The proceeding at: IEEE International Conference on Communications (ICC), tool place 2014, June, 10-14 in Sidney (Australia).A cooperative blind interference alignment (BIA) strategy is considered for the downlink of cellular systems. The aim is to reduce intercell interference in order to protect users, especially at the cell edge. The strategy consists of appropriately splitting the available bandwidth and is shown to be well-suited to scenarios where the number of cell-edge users is considerable. For a system comprising two cells each with a base station of Nt antennas, it is shown that, compared to a previous augmented code approach where transmission to all users occurs in the same frequency band, the proposed strategy leads to better rates over a wide range of signal-to-noise ratios when the number of cell-edge users in both cells exceeds 2Nt -1.This work has been partially funded by research projects COMONSENS (CSD2008-00010) and GRE3N (TEC2011-29006-C03-02). This research work was partly carried out at the ESAT Laboratory of KU Leuven in the frame of the Belgian Programme on Interuniversity Attractive Poles Programme initiated by the Belgian Science Policy Office: IUAP P7/23 ‘Belgian network on stochastic modeling analysis design and optimization of communication systems’(BESTCOM) 2012-2017.Publicad

Cognitive Blind Interference Alignment for Macro-Femto Cellular Networks

The proceeding at: 2014 IEEE Global Communications Conference took place 8-12 December 2014 in Austin, TX, USA.A cognitive Blind Interference Alignment scheme is devised for use in macro-femto cellular networks. The proposed scheme does not require any channel state information at the transmitter or data sharing among the Macro Base Station and the Femto Access Points. It achieves transmission to femto cell users without affecting the rates of the Macro users. This is achieved by appropriately combining the supersymbols of the Macro Base Stations and the Femto Access Points. It is shown that in some scenarios the use of this scheme results to considerable rates for Femto users.This work has been partially funded by research projects COMONSENS (CSD2008-00010) and GRE3N (TEC2011-29006-C03-02). This research work was partly carried out at the ESAT Laboratory of KU Leuven in the frame of the Belgian Programme on Interuniversity Attractive Poles Programme initiated by the Belgian Science Policy Office: IUAP P7/23 ‘Belgian network on stochastic modeling analysis design and optimization of communication systems’ (BESTCOM) 2012-2017.Publicad

Blind Interference Alignment for Cellular Networks

We propose a blind interference alignment scheme for partially connected cellular networks. The scheme cancels both intracell and intercell interference by relying on receivers with one reconfigurable antenna and by allowing users at the cell edge to be served by all the base stations in their proximity. An outer bound for the degrees of freedom is derived for general partially connected networks with single-antenna receivers when knowledge of the channel state information at the transmitter is not available. It is demonstrated that for symmetric scenarios, this outer bound is achieved by the proposed scheme. On the other hand, for asymmetric scenarios, the achievable degrees of freedom are not always equal to the outer bound. However, the penalty is typically small, and the proposed scheme outperforms other blind interference alignment schemes. Moreover, significant reduction of the supersymbol length is achieved compared with a standard blind interference alignment strategy designed for fully connected networks.This work has been partially funded by research projects COMONSENS (CSD2008-00010) and GRE3N (TEC2011-29006-C03-02). This research work was partly carried out at the ESAT Laboratory of KU Leuven in the frame of the Belgian Programme on Interuniversity Attractive Poles Programme initiated by the Belgian Science Policy Office: IUAP P7/23 ‘Belgian network on stochastic modeling analysis design and optimization of communication systems’ (BESTCOM) 2012–2017. The work of D. Toumpakaris was supported by the European Union (European Social Fund—ESF) and Greek national funds through the Operational Program Education and Lifelong Learning of the National Strategic Reference Framework through the Research Funding Program Thales—Investing in knowledge society through the European Social Fund. The work of Syed Jafar was supported in part by NSFgrants CCF-1319104 and CCF-1317351.Publicad